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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        Tool Citations

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        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.29

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        REPORTE DE MUESTRA

        Nombre
        Thalassomics
        Contacto
        info@thalassomics.com
        Sitio Web
        https://github.com/trippv/integrity_massively
        Tipo de proyecto
        RNA-seq
        Platafora
        HiSeq 2500 High Output V4
        Setup
        2x125

        General Statistics

        Showing 12/12 rows and 8/10 columns.
        Sample Name% Duplication% > Q30Mb Q30 basesReads After FilteringGC content% PF% AdapterFrag Length% AlignedM Aligned
        batch1_R1
        167.6bp
        99.9%
        0.0M
        batch1_chrI
        0.0%
        92.8%
        7.6Mb
        0.1M
        43.4%
        99.4%
        1.5%
        batch2_R1
        170.8bp
        99.9%
        0.1M
        batch2_chrI
        0.0%
        92.9%
        10.6Mb
        0.1M
        43.4%
        100.0%
        0.6%
        batch3_R1
        167.4bp
        99.9%
        0.0M
        batch3_chrI
        0.0%
        92.8%
        8.1Mb
        0.1M
        43.6%
        99.5%
        1.4%
        chem1_R1
        166.8bp
        99.9%
        0.0M
        chem1_chrI
        0.0%
        92.9%
        6.7Mb
        0.1M
        43.4%
        100.0%
        0.7%
        chem2_R1
        172.5bp
        99.9%
        0.0M
        chem2_chrI
        0.0%
        93.1%
        8.4Mb
        0.1M
        43.3%
        100.0%
        0.5%
        chem3_R1
        173.5bp
        99.9%
        0.1M
        chem3_chrI
        0.0%
        93.1%
        10.1Mb
        0.1M
        43.4%
        100.0%
        0.6%

        fastp

        Version: 0.23.4

        All-in-one FASTQ preprocessor (QC, adapters, trimming, filtering, splitting...).URL: https://github.com/OpenGene/fastpDOI: 10.1093/bioinformatics/bty560

        Fastp goes through fastq files in a folder and perform a series of quality control and filtering. Quality control and reporting are displayed both before and after filtering, allowing for a clear depiction of the consequences of the filtering process. Notably, the latter can be conducted on a variety of parameters including quality scores, length, as well as the presence of adapters, polyG, or polyX tailing.

        Filtered Reads

        Filtering statistics of sampled reads.

        Created with MultiQC

        Insert Sizes

        Insert size estimation of sampled reads.

        Created with MultiQC

        Sequence Quality

        Average sequencing quality over each base of all reads.

        Created with MultiQC

        GC Content

        Average GC content over each base of all reads.

        Created with MultiQC

        N content

        Average N content over each base of all reads.

        Created with MultiQC

        BUSCO

        Version: 5.8.2

        Assesses genome assembly and annotation completeness.URL: http://busco.ezlab.orgDOI: 10.1093/bioinformatics/btv351

        BUSCO v2 provides quantitative measures for the assessment of genome assembly, gene set, and transcriptome completeness, based on evolutionarily-informed expectations of gene content from near-universal single-copy orthologs selected from OrthoDB v9.

        Lineage: eukaryota_odb10

        Created with MultiQC

        Kallisto

        Quantifies abundances of transcripts (or more generally, of target sequences) from RNA-Seq data.URL: http://pachterlab.github.io/kallistoDOI: 10.1038/nbt.3519

        Created with MultiQC

        Pca Plot

        Análisis de Expresión Diferencial

        PCA de expresión génica

        El gráfico de PCA (Análisis de Componentes Principales) permite visualizar cómo se agrupan las muestras según su perfil de expresión génica. Muestras cercanas entre sí tienen patrones de expresión similares, lo que puede reflejar similitudes biológicas o técnicas entre los grupos.

        Expresión diferencial

        El volcano plot muestra los genes diferencialmente expresados entre dos grupos. Cada punto representa un gen: el eje X indica el cambio en la expresión (log₂ Fold Change), y el eje Y indica la significancia estadística (-log₁₀ p-valor ajustado). Los genes más alejados y en rojo son los más significativamente regulados.

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        SoftwareVersion
        BUSCO5.8.2
        fastp0.23.4

        MultiQC v1.29 - Written by Phil Ewels, available on GitHub.

        This report uses Plotly, jQuery, jQuery UI, Bootstrap and FileSaver.js.